My research seeks to improve the effectiveness and equity of interventions for social good through data and analytics. One area of focus is improving access to, and consumption of, fresh food, by optimizing incentive and subsidy programs. Much of this work has been motivated through collaborations with the Massachusetts Department of Transitional Assistance. Another stream of research uses machine learning and optimization to improve refugee resettlement. This work is in collaboration with the GeoMatch team at the Stanford Immigration Policy Lab, where I completed a postdoc. Beyond these applications, I am broadly interested in the design and allocation of resources in social good settings. My research intersects various fields including machine learning, optimization, economics, and statistics.

I received my PhD in Operations Research from MIT in 2021, where I was co-advised by Retsef Levi and Georgia Perakis. Before coming to MIT, I received a B.S. in Math, B.S. in Statistics, and M.A. in Math from the Pennsylvania State University.

You can find my CV here.

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Research

Working papers

• Public Opinion on Fairness and Efficiency for Algorithmic and Human Decision-Makers. Preprint.
  With Kirk Bansak
• Group fairness in dynamic refugee assignment. Preprint.
  With Daniel Freund, Thodoris Lykouris, Bradley Sturt, and Wentao Weng
  • Extended abstract appeared at the 24th ACM Conference on Economics and Computation (EC), 2023
  • Extended abstract appeared at the 4th annual Symposium on Foundations of Responsible Computing (FORC), 2023
• Dynamic Matching with Post-Allocation Service and its Application to Refugee Resettlement. Preprint.
  With Kirk Bansak, Soonbong Lee, Vahideh Manshadi, and Rad Niazadeh
• Optimal Interventions for Increasing Healthy Food Consumption Among Low-Income Populations. Preprint.
  With Retsef Levi and Georgia Perakis
  • Accepted for oral presentation, 4th Workshop on Mechanism Design for Social Good (MD4SG '20)
  • Finalist, POMS College of Sustainable Operations Best Student Paper Competition, 2021
  • Finalist, IBM Best Student Paper Award, 2019
• Reverse Information Sharing: Reducing Costs in Supply Chains with Yield Uncertainty. Preprint.
  With Pavithra Harsha, Ashish Jagmohan, Retsef Levi, and Georgia Perakis
  • 2nd place, POMS College of Supply Chain Management Best Student Paper Competition, 2021

Published

• Learning Under Random Distributional Shifts. Link.
  With Kirk Bansak and Dominik Rothenhäusler
  To appear in the proceedings of AISTATS 2024
• Outcome-Driven Dynamic Refugee Assignment with Allocation Balancing. Link.
  With Kirk Bansak
  Operations Research (Accepted, 2024)

  • Extended abstract appeared at the 23rd ACM Conference on Economics and Computation (EC), 2022
• Public Health Risks Arising from Food Supply Chains: Challenges and Opportunities. Link.
  With Lu Chen, Donovan Guttieres, Retsef Levi, Georgia Perakis, Nicholas Renegar, and Stacy Springs
  Naval Research Logistics (special issue on OR Models in Developmental Studies), 2021
• A Game Theoretic Model for Resource Allocation Among Countermeasures with Multiple Attributes. Link.
  With Jeffrey Keisler and Igor Linkov
  European Journal of Operations Research, 2016
• Cooperation Can Emerge in Prisoner’s Dilemma from a Multi-Species Predator Prey Replicator Dynamic. Link.
  With Christopher Griffin
  Mathematical Biosciences, 2016
• Deriving an Optimally Deceptive Policy in Two-Player Iterated Games. Link.
  With Christopher Griffin
  In proceedings of American Control Conference, 2016
• Optimal Process Control of Symbolic Transfer Functions. Link.
  With Christopher Griffin
  In proceedings of Feedback Computing, 2015
• Better Timing of Cyber Conflict. Link.
  With Christopher Griffin
  In proceedings of Third ASE International Conference on Cyber Security, 2014

Media

• "Can Government Programs Get People to Eat More Healthily?" (Chicago Booth Review)
• "Unequal Access to Food" (MIT Sloan Year in Review).
• "Using Machine Learning to Help Refugees Succeed" (Stanford HAI).